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Writing and presenting results is important for any research work. Publishing is not enough; it should be written clearly and consistently for others to read and cite. We present a review of different techniques, for improving the writing in research papers intended for publishing. These include how to write the title, whether to use active or passive voice, how long sentences should be, how to present the uncertainty, understanding the International System of Units (SI) writing conventions, how to assign authorship, how to effectively use references, how to present the work, and how to publish it in a journal. This paper is a summary of the main and most recent recommendations in the scientific field on how to write a research paper to increase its impact.

Supercapacitors are favored by researchers because of their high power density, especially with the acceleration of people's life rhythm. However, their energy density, especially from the point of view of the whole energy storage device, is far lower than that of commercial batteries. In this work, a kind of customizable full paper-based supercapacitor device with excellent self-healing ability is fabricated by simple and low-cost screen printing, electropolymerization and dip coating methods. The resultant separator-free supercapacitor device exhibits both ultrahigh gravimetric and areal specific energy (power) densities of 39 Wh kg−1 (69 kW kg−1) and 692 μWh cm−2 (236 mW cm−2), achieving excellent supercapacitor performance. Notably, the addition of vitrimers endows the whole device with outstanding self-healing properties, which is helpful for enhancing the adaptability of the device to the environment. In addition, this kind of paper-based device also displays good photothermal and electromagnetic shielding performances. These striking features make paper matrix composites attractive in the fields of supercapacitors, medical photothermal treatment and electromagnetic shielding.

In recent times, it has been witnessed that wireless systems based on IoT-based have developed rapidly in various sectors. The IoT (Internet of Things) is the network in which physical devices, equipment, sensors and other objects can communicate among themselves without human involvement. The WSN (Wireless Sensor Network) is a central component of the IoT, which has proliferated into several different applications in real-time. The IoT and WSNs now have various critical and non-critical applications impacting nearly every area of our everyday life. WSN nodes are usually small and battery-driven machines. Thus, the energy effective data aggregation techniques that increase the lifespan of the network are highly significant. Various approaches and algorithms for energy-efficient data aggregation in IoT-WSN systems were presented. This paper reviews the literature with specific attention to aspects of wireless networking for the preservation of energy and aggregation of data.

Photonic crystals film that possesses periodic dielectric structure have shown great prospect in developing environmentally friendly paper alternatives due to the unique properties of dye free and non-photobleaching, but their practical application is limited by the weak interaction between colloidal particles. Although some progress has been obtained, it is still a challenge to develop photonic paper with the desired mechanical and optical properties. Herein, multifunctional hard core/soft shell nanoparticles with controlled size are fabricated by semi-continuous seed emulsion polymerization method. Compared with convention colloidal particles, these core/shell nanoparticles can facile self-assemble into large-scale dense ordered structure film via dried at room temperature due to the relatively low glass transition temperature (Tg) of the shell layers. The facile fabrication route enables the continuous high-through put production of the photonic papers. The as-formed papers not only possess the capacity to solvent (water/ethanol) rewritable and multicolor painting, but also can rapidly reversible mechanochromic. Moreover, due to the good compatibility of core/shell interface, these photonic films possess excellent mechanical properties, demonstrating that this multifunctional film makes the fabrication of novel robust rewritable papers possible and enables visual monitoring of deformation degree.

Thermal papers are replacing the conventional form of printing and are being extensively used across the globe. This study encompasses a non-destructive approach to examine thermal papers by using ATR-FTIR spectroscopy and Video Spectral Comparator (VSC), where the former technique helps in characterizing and discriminating different samples and the latter helps in deciphering the faded prints on thermal paper. The qualitative analysis of the spectroscopic data based on peak to peak comparison and quantitative analysis using chemometrics has been done to obtain high discriminating power. Multivariate analysis using HCA gave a discriminating power of 83.82% and PCA showed a variance of 95.64%. The strength of the study is portrayed through the decipherment of artificially and naturally faded thermal papers using VSC and analyzing the effect of different storing conditions on their rate of fading.

Flexible paper-based surface enhanced Raman spectroscopy (SERS) substrate has attracted great attention in the sensitive detection of analytes in recent years. However, due to its inherent hydrophilic surface, the nanoparticles will not be concentrated very well on the surface of the paper. This reduces the reproducibility and sensitivity of the paper-based substrate. Herein, we demonstrate flexible hydrophobic paper-based substrate using silver nanocubes loaded on polymethylhydrosiloxane modified filter paper (AgNCs@SiO2/PMHS modified filter paper) to realize high sensitivity and reproducibility. The hydrophobic filter paper was obtained by dip-soaking the filter paper into PMHS solution, resulting in increased contact angle to ~112.5°. The AgNCs@SiO2/PMHS modified paper substrate shows high analytical enhancement factor (AEF) of 6.55 × 106, which is 2.2-fold enhancement compared to AgNCs@SiO2/normal paper substrate, and a low detection limit of 0.1 nM rhodamine 6G and 0.89 nM adenine. The high SERS enhancement factor and sensitivity is attributed to the high hotspots density created in the hydrophobic surface as a result of the excellent uniformity and superior sample collection efficiency compared to the normal filter paper-based substrate. Besides, the substrate shows excellent spot-to-spot and substrate-to-substrate reproducibility, with relative standard deviation (RSD) of 6.05% and 9.22%, respectively. Moreover, the AgNCs@SiO2/PMHS modified filter paper substrate achieved good stability; the Raman signal intensity only drops by 25.88% after 3 months of exposure to air. Therefore, this flexible hydrophobic AgNCs@SiO2/PMHS modified filter paper substrate with low cost fabrication and label-free SERS detection is a promising SERS platform for analytical and biological sensing applications.

Graphene-based papers have recently triggered considerable interests in developing the application as thermal interface materials (TIMs) for addressing the interfacial heat transfer issue, but their low through-plane thermal conductivity (κ⊥), resulting from the layer-by-layer stacked architecture, limits the direct use as TIMs. Although various hybrid graphene papers prepared by combining the graphene sheets and the thermally conductive insertions have been proposed to solve this problem, achieving a satisfactory κ⊥ higher than that of commercial TIMs (>5 W m−1 K−1) remains challenging. Here, a strategy aimed at the construction of heat pathways along the through-plane direction inside the graphene paper for achieving a high κ⊥ was demonstrated through the simultaneous filtration of graphene sheets with two different lateral sizes. The as-prepared graphene paper presented a hierarchical structure composed of loosely stacked horizontal layers formed by large graphene sheets, intercalated by a random arrangement of small graphene sheets. Due to the heat pathways formed by small graphene sheets along the through-plane direction, the hierarchically structured graphene paper exhibited an improved κ⊥ as high as 12.6 W m−1 K−1 after a common graphitization post-treatment. In the practical test, our proposed paper as an all-graphene TIM achieved an enhancement in cooling efficiency of ≈ 2.2 times compared to that of the state-of-the-art TIM, demonstrating its superior performance to meet the ever-increasing heat dissipation requirement.

This paper presents a critical review of laser pyrolysis. Although this technology is almost 60 years old, in literature many researchers, both from academia and industry, are still developing and improving it. On the contrary industrial applications are struggling to take off, if not in very restricted areas, although the technology has undoubted advantages that justify future development. The aim of this work consists in analysing a representative pool of scientific papers (230) and patents (121), from the last 20 years, to have an overview about the evolution of the method and try to understand the efforts spent to improve this technology effectively in academia and in industry. This study is important to provide a complete review about the argument, still missing in the literature. The objective is to provide an overview sufficiently broad and representative in the sources and to capture all the main ways in which laser pyrolysis has been used and with what distribution. The main focuses of the study are the analyses of the functions carried out by laser technologies, the application fields, and the types of used laser (i.e. models, power and fluence). Among the main results, the study showed that the main use of laser pyrolysis is to produce nanoparticles and coatings, the main materials worked by laser pyrolysis are silicon and carbon dioxide and the main searched properties in the products of laser pyrolysis are catalysts activity and electrical conductivity. CO2 lasers are the most used and the have high versatility compared to others. In conclusion, the study showed that laser pyrolysis is a consolidated technology within its main application fields (nanoparticles and coatings) for several years. Within this context, the technology has been developed on very different sizes and processes, obtaining a very wide range of results. Finally, these results may also have stimulated new areas of experimentation that emerged mainly in recent years and which concern biomedical applications, additive manufacturing, and waste disposal. Graphical abstract

Rational design of photoelectrode architectures is deemed as an effective solution to enhance efficiency of photoelectrochemical water splitting for conquering increasingly prominent environmental problems. Herein, a programmable flexible photoanode with built-in tandem Z-scheme configuration fabricated by in-situ growth of MoSe2-CdS-ZnO array with ultrathin nanosheet-interlaced-nanorod structure on the Au paper electrode, is firstly reported. By taking advantages of the interwoven nanonetwork structure, high conductivity as well as larger porosity of the as-fabricated Au paper electrode, a stable light-harvesting paper chip with fast transfer/separate mediators of the charge/carriers is thus integrated. By virtue of double internal electric fields (IEFs) and photothermal effect, the developed MoSe2-CdS-ZnO photoanode exhibits incident-photon-to-current efficiency of 52 % under 460 nm of light irradiation, and the current density reaches 2.4 mA cm−2 at 0.3 V versus normal hydrogen electrode, which is comparable with respect to current state-of-the-art “type-II-scheme”, “surface-scheme”, and cocatalyst-free photocatalysts (0.03–2.4 mA cm−2). Consequently, the paper-based photoanode achieves admirable photoelectrocatalytic hydrogen generation property (39.7 μmol cm−2 h-1). The synergistic effect of tailorable tandem Z-scheme configuration with double IEFs and delineating of 3D cross-linked network structure of the proposed photoanode in this work may open an avenue for constructing high-performance photoelectrochemical water splitting devices.

We preliminarily examined whether it is possible to visualize synthetic materials applied to the surface of a base material by using near-infrared hyperspectral imaging at wavelengths of 1.0–2.35 µm. We focused on the applicability of this method for visualizing adhesives and varnishes, assessing the effect of underlying colorants on measurements, and selecting the optimal method for data analysis. Experimental samples were adhesive on a painted ceramic plate and varnish on printed paper. We performed correlation analysis, partial least squares regression analysis, linear discriminant analysis, decision tree, KNN and principal component scores 1 and 2 to evaluate the measurement data. The conventional method (visible/near-infrared spectroscopic/fluorescence photographs at wavelengths of 400–1000 nm.) could not visualize the adhesive on the painted ceramic plate or the varnish on the printed paper, whereas the new method could do so. Therefore, this method has the potential to be useful for inspecting the distribution of synthetic materials on the surface of a base material.

Bacteria identification has predominantly been conducted using specific bioreceptors such as antibodies or nucleic acid sequences. This approach may be inappropriate for environmental monitoring when the user does not know the target bacterial species and for screening complex water samples with many unknown bacterial species. In this work, we investigate the supervised machine learning of the bacteria-particle aggregation pattern induced by the peptide sets identified from the biofilm-bacteria interface. Each peptide is covalently conjugated to polystyrene particles and loaded together with bacterial suspensions onto paper microfluidic chips. Each peptide interacts with bacterial species to a different extent, leading to varying sizes of particle aggregation. This aggregation changes the surface tension and viscosity of the liquid flowing through the paper pores, altering the flow velocity at different extents. A smartphone camera captures this flow velocity without being affected by ambient and environmental conditions, towards a low-cost, rapid, and field-ready assay. A collection of such flow velocity data generates a unique fingerprinting profile for each bacterial species. Support vector machine is utilized to classify the species. At optimized conditions, the training model can predict the species at 93.3% accuracy out of five bacteria: Escherichia coli, Staphylococcus aureus, Salmonella Typhimurium, Enterococcus faecium, and Pseudomonas aeruginosa. Flow rates are monitored for less than 6 s and the sample-to-answer assay time is less than 10 min. The demonstrated method can open a new way of analyzing complex biological and environmental samples in a biomimetic manner with machine learning classification.

Flexible all-solid-state supercapacitors (FASSCs) have attracted much attention as power supplies for portable and wearable electronic products. Herein, we report the fabrication of a foldable, extra lightweight, flexible chopped carbon fiber paper (CFP) with a porous network structure prepared via wet-mold papermaking that can serve as a conductive substrate. The conductivity and pseudocapacitance of the electrode were improved by controlling the growth of 3D Cu(OH)2 nanorod arrays on CFP substrate. The Cu(OH)2@CFP electrode has a high specific capacitance of 421.8 mF cm−2 at a current density of 0.5 mA cm−2 with capacitance retention of 82.98% at a current density of 10 mA cm−2 after 5000 charge-discharge cycles. The FASSC manifested not only a large capacitance of 196.1 mF cm−2 at 2 mA cm−2, as well as energy and power densities of 6.97 × 10−2 mWh cm−2 and 1.6 mW cm−2, respectively, but also excellent stability of 80.3% over 5000 cycles at 5 mA cm−2. In addition, we confirmed that the FASSC has a large bending angle and can be twisted into various shapes, thereby indicating its applicability in portable and wearable electronic devices.

Biorefinery is pivotal to the sustainability of modern chemical industry. However, since biomass is oxygen-enriched, new and green chemical strategies are required for expanding the biomass derived chemical space. In this work, synthesis of natural products dihydrocapsaicin and dihydrocapsiate was achieved exclusively from lignocellulosic platform chemicals. Natural products dihydrocapsaicin and dihydrocapsiate were synthesized exclusively from lignocellulosic platform chemicals, using furfural (from hemicellulose) and methyl isopropyl ketone (from cellulose) through aldol condensation-hydrolysis-hydrodeoxygenation to synthesize 8-methylnonanoic acid and then combined with vanillin derivates (from lignin). This synthesis demonstrates the feasibility of constructing natural products entirely from renewable biomass platform through green processes. The utilization of inherent functional groups of biomass demonstrates their potential to open up chemical space.

In this study, the effects of corrosion inhibitor of sludge produced in the process of natural gas exploitation and transportation on sulfur oxidation by Acidithiobacillus thiooxidans were studied....

Flexible thermoelectric materials are presented with potential applications in electronic devices and energy conversion due to their convenient preparation, good flexibility, and various forms. However, as ductility is rarely observed in inorganic semiconductors and ceramic insulators, reports on applications of inorganic oxide materials in flexible thermoelectric materials are sparse. Here, we report a new method for the synthesis of a flexible Na1.4Co2O4 thermoelectric material based on Na1.4Co2O4 bulk materials, which are prepared by a self-flux method and painted on print paper. Seebeck coefficient and power factor of the obtained thermoelectric material are 78–102 μVK-1 and 159–223 μWm-1K-2, respectively, in a temperature range of 303–522 K, which are superior to those values of other conductive polymers and their compounds. More interestingly, the n-type Na1.4Co2O4 flexible material is obtained in the painting process at higher pressure with Seebeck coefficients of –109 to –183 μVK-1 in a temperature range of 303–522 K. The convenient preparation method of these novel flexible thermoelectric materials may be expanded to the synthesis of other flexible thermoelectric materials, which will be the focus of future work.

In recent years, agricultural wastes cause serious pollution to the environment. Agricultural residues can be used to produce value-added products in order to control environmental pollution, therefore these wastes are a promising feedstock as it has many advantages such as wide range of source, low cost and renewable. Rice straw and lemongrass leaves which are the renewable sources for the production of many useful products such as xylose. The aim of this study is to compare the content of xylose produced from rice straw and lemongrass leaves, in order to obtain highest yield of xylose and to optimize the acid hydrolysis time, concentration of sulphuric acid, liquid–solid ratio and the power of the microwave towards the maximum extraction of xylose. Microwave assisted acidic hydrolysis method was used to extract xylose from rice straw and lemongrass leaves. The acid hydrolysis of both rice straw and lemongrass was performed at different time (1–5 min), acid concentration (1%–5%), liquid solid ratio (1:30, 2:30, 3:30, 4:30 and 5:30) and power (160 W, 320 W, 480 W, 640 W, 800 W). The results obtained indicate that the yield of xylose from rice straw (2.98 g/L) via the microwave assisted is slightly higher than lemongrass (2.91 g/L) with optimum conditions of 3 min of hydrolysis time, 2% of sulphuric acid concentration, 1:30 of liquid solid ratio and 320 W of microwave power. Meanwhile, the optimum conditions for lemongrass leaves are 4 min of hydrolysis time, 4% of sulphuric acid concentration, 2:30 of liquid solid ratio and 480 W of microwave power. Thus, rice straw has slightly higher capability in production of xylose compared to lemongrass.

The alternative and renewable sources of energy are very much essential to reduce the dependency on fossil fuels and also to control the environmental pollution. One of the important renewable sources which replace the fossil based fuels is biodiesel. The biodiesel is highly influenced by fatty acid composition. Hence, in the present work Salvodara persica nonedible seed oil (38% oil content) which is rich in saturated fatty acids (79.16%) is mixed with Leucas aspera nonedible seed oil (22.50% oil content), which is rich in unsaturated fatty acids (90.72%) in equal proportion (1:1). The mixed seed oil fatty acid profile is analyzed by GC-FID which shows that, it is exactly half of the fatty acid profile of individual seed oils (saturation 45.26% and unsaturation 54.74%). Bio-mixed oil is transesterified and the biodiesel produced is characterized for its fuel properties. The fuel properties of biodiesel produced from mixed seed oils is compared with biodiesel from individual seed oils, already existing biodiesels and biodiesel standards. It reveals that better quality biodiesel is produced by mixing seed oil strategy. Even the emission analysis shows that the emissions are reduced except NOx. This work reveals that it is one of the important criterions to improve the biodiesel quality by mixed seed oil strategy.

A computational method that directly translates the scattering peak information to crystalline domain shapes and orientations is presented. The method is demonstrated at a synchrotron beamline with a standard X-ray scattering setup., Characterization of thin films is of paramount importance for evaluating material processing outcomes/efficiency as well as establishing structure–property/performance relationships. This article introduces grazing-incidence diffraction tomography (GID tomography), a technique that combines grazing-incidence X-ray scattering and computed tomography to quantitatively determine the dimension and orientation of crystalline domains in thin films without restrictions on the beam coherence, substrate type or film thickness. This computational method extends the capability of synchrotron beamlines by utilizing standard X-ray scattering experiment setups.

During use, textile items can develop unpleasant odors that arise from many different sources, both internal and external to the human body. Laundering is not always effective at removing odors, with odor potentially building up over time due to incomplete removal of soils and odorous compounds and/or malodors transferred during the laundering process. Textile odor can lead to consumer dissatisfaction, particularly as there are high expectations that clothing and textile products meet multiple aesthetic and functional needs. The problem of odor in textiles is complex and multi-faceted, with odorous volatile compounds, microorganisms, and precursors to odor, such as sweat, being transferred to, and retained by, fabrics. This article reviews the literature that specifically relates to odor within textiles. Methods for evaluating odor in textiles, including methods for collecting odor on textile substrates, as well as sensory and instrumental methods of odor detection, were reviewed. Literature that examined differences among fabrics that varied by fabric properties were reviewed. As well, the effectiveness of specific odor controlling finishing technologies to control malodor within textiles was also examined.

Environmental concern for our planet has changed significantly over time due to climate change, caused by an increasing population and the subsequent demand for electricity, and thus increased power generation. Considering that natural gas is regarded as a promising fuel for such a purpose, the need to integrate carbon capture technologies in such plants is becoming a necessity, if gas power plants are to be aligned with the reduction of CO2 in the atmosphere, through understanding the capturing efficacy of different absorbents under different operating conditions. Therefore, this study provided for the first time the comparison of available absorbents in relation to amine solvents (MEA, DEA, and DEA) CO2 removal efficiency, cost, and recirculation rate to achieve Climate change action through caron capture without causing absorbent disintegration. The study analyzed Flue under different amine-based solvent solutions (monoethanolamine (MEA), diethanolamine (DEA), and methyldiethanolamine (MDEA)), in order to compare their potential for CO2 reduction under different operating conditions and costs. This was simulated using ProMax 5.0 software modeled as a simple absorber tower to absorb CO2 from flue gas. Furthermore, MEA, DEA, and MDEA adsorbents were used with a temperature of 38 &deg, C and their concentration varied from 10 to 15%. Circulation rates of 200&ndash, 300 m3/h were used for each concentration and solvent. The findings deduced that MEA is a promising solvent compared to DEA and MDEA in terms of the highest CO2 captured, however, it is limited at the top outlet for clean flue gas, which contained 3.6295% of CO2 and less than half a percent of DEA and MDEA, but this can be addressed either by increasing the concentration to 15% or increasing the MEA circulation rate to 300 m3/h.

We investigated the use of dielectric layers produced by atomic layer deposition (ALD) as an approach to strain mitigation in composite silicon/superconductor devices operating at cryogenic temperatures. We show that the addition of an ALD layer acts to reduce the strain of spins closest to silicon/superconductor interface where strain is highest. We show that appropriately biasing our devices at the hyperfine clock transition of bismuth donors in silicon, we can remove strain broadening and that the addition of ALD layers left T 2 (or temporal inhomogeneities) unchanged in these natural silicon devices.

Lignocellulose, as the most abundant type of inedible biomass, is considered as a promising renewable feedstock for making fuels, chemicals, and materials. However, its complex structure makes most of current biorefinery processes suffer from low resource utilization rates, high energy consumption or ill-defined market orientation of the obtained products. Here, we propose and evaluate the EXA (Ethanol, Xylose, Adhesive) biorefinery strategy based on current xylose industry. This process integrates four conversion and separation stages to consecutively produce ethanol, xylose, and adhesive with total carbon utilization of 79.6%. The key innovation is the establishment of an easy-to-operate process for direct production of high-quality adhesive from a lignin-rich liquid fraction that makes the overall process significantly more sustainable. Techno-economic analysis (TEA) shows that the revenue of proposed EXA process increases more than 110 times compares with the current process and life cycle assessment (LCA) demonstrates a much lower CO2 footprint from an environmental burden per unit of revenue perspective.

It is widely accepted that plastic waste is one of the most urgent environmental concerns the world is currently facing. The emergence of bio-based plastics provides an opportunity to reduce dependency on fossil fuels and transition to a more circular plastics economy. For polyethylene terephthalate (PET), one of the most prevalent plastics in packaging and textiles, two bio-based alternatives exist that are similar or superior in terms of material properties and recyclability. These are polyethylene furanoate (PEF) and polytrimethylene terephthalate (PTT). The overarching aim of this study was to examine the transition from fossil-based to renewable plastics, through the lens of PET upcycling into PEF and PTT. The process for the production of PEF and PTT from three waste feed streams was developed in the SuperPro Designer software and the economic viability assessed via a discounted cumulative cash flow (DCCF) analysis. A techno-economic analysis of the designed process revealed that the minimum selling price (MSP) of second generation-derived PEF and PTT is 3.13 USD/kg, and that utilities and the feedstock used for the production of 2,5-furandicarboxylic acid (FDCA) needed in PEF synthesis contributed the most to the process operating costs. The effect of recycling PEF and PTT through the process at three recycling rates (42%, 50% and 55%) was investigated and it was revealed that increased recycling could reduce the MSP of the 2G bio-plastics (by 48.5%) to 1.61 USD/kg. This demonstrates that the plastic biorefinery, together with increasing recycling rates, would have a beneficial effect on the economic viability of upcycled plastics.

International audience; In Normandy, the marine macroalgae become a large problem when the retreat of the tide leaves large quantities of stranded seaweed on coast. These stranded seaweeds can be toxic during their degradation in addition to creating odor problems. Consequently, their elimination has become a major problem and their recovery an emergency. In this work, we proposed to use the stranded seaweed in the building construction at a large scale. We investigated in particular the performance of insulated walls based on lightened earth incorporating reed and stranded Laminaria digitata seaweed at different substitution level. The compressive strength and the hygrothermal properties of the earth insulated walls specimens were carried out. Our results show that the incorporation of seaweed in lightened earth improves both its heat storage capacity and its level of insulation without compromising its compressive strength. The most efficient seaweed content for improving the thermal insulation of the material seems to be 20%. Indeed, the addition of 20% of Laminaria digitata decreased the thermal conductivity by 34% at 20 °C in comparison with standard cob. For this mixture, the specific heat capacity value is around 800 J.kg−1.K−1 at 20 °C, which are very high compared to that of the only earth-fiber specimen (400 J.kg−1.K−1). These increases in mechanical and hygrothermal performance of insulating cob material incorporating seaweed will lead to a reduction of the cob walls thickness and therefore to the development of sustainable energy efficient building materials with a low environmental impact.

Treatment of the huge amount of cellulose waste is an urgent challenge. Here, cellulose waste is used to prepare photocatalyst for molecular O2 activation by using a sulfuric acid-assisted hydrothermal method. The product can activate O2 to produce superoxide anion ( O2−), which can be subsequently used in Cr(VI) pollution remediation effectively by reducing it into Cr(III). The Cr(VI) removal efficiency can reach 90 % in 100 min. This is important to achieve sustainable utilization of O2 and solar energy. Compared with glucose, cellulose is a superior raw material for the synthesis of photocatalytic acid-HTCC. It exhibits higher reduction power due to its more negative conduction band edge. This low-cost, easy to prepare, and environment friendly acid-HTCC could have promising applications in environmental treatments. This work successfully turns waste into wealth, relieving the environmental concerns of cellulose waste, and provides a way to solve the urgent environmental pollution at present.

In this study, the production of fermentable sugars and biogas from thermally pretreated brewer’s spent grains (BSGs) was investigated. There were two autohydrolysis conditions (C1-1S: 180 oC, 30 min, 5 mLH2O gBSG−1 and C2-1S: 180 oC, 60 min, 5 mLH2O gBSG−1) which were evaluated, with and without a previous low severity pretreatment (80 oC, 10 min, 10 mLH2O gBSG−1). The highest specific methane production (302.4 NLCH4 kgCOD−1) and enzymatic hydrolysis yield (EHY of 98%, 50 FPU gBSG−1) were obtained from the two-stage pretreatment, with the second stage operated at 180 °C for 60 min, 5 mLH2O gBSG−1. However, in the integrated process, the two-stage pretreatment with the second stage performed at 180 °C for 30 min, and 5 mLH2O gBSG−1 was the best condition to produce fermentable sugars from enzymatic hydrolysis of pretreated BSGs, using a lower enzyme loading (EHY of 93%, 25 FPU gBSG−1). The burning of biogas produced from an anaerobic digestion of liquid fractions (hydrolysates) generated after two-stage thermal pretreatment in a combined heat and power system can produce a net thermal energy of 1.71 MJ kgBSG dry basis−1 and electrical energy of 0.392 kW h kgBSG dry basis−1.

Innovative removal of toxic nitrite and ammonia is one of the key approaches for efficient aquaculture biotechnology. This study suggests a fast removal technique of high-levels of nitrite and ammonia using recirculating aquaculture wastewater at 30‰ salinity. Four lab-scale moving bed biofilm reactors (MBBRs; R1, R2, R3, and R4) were operated in parallel for 56 days with different combinations of mature and fresh biofilms on biocarriers at 30% filling ratio. Nitrogen removal efficiency, biofilm physicochemical properties, and microbial analyses were conducted using PCR and sequencing techniques at the region of the 16S ribosomal RNA. The results showed that R4 (using mature biofilms) recorded the highest nitrite and ammonia removal (99.6% and 95.3%, respectively) compared to the control, R1 (94.1% and 89.4%). Meanwhile, the removal rate of ammonia in R4 was significantly the fastest compared to other reactors. Partial Least Squares-Discriminant Multivariate Analysis (PLS-DA) model showed a good prediction with very high accuracy and prediction (Q2 > 0.8) for the first three principal components pertaining to nitrite and ammonia removal. Planktosalinus genus was the most abundant in R4, while proteobacteria phylum was the dominant, followed by Marinobacter and Nitrospina in all reactors. Overall, the use of mature biofilms in MBBR was proven to increase bacterial diversity, enhancing nitrite and ammonia removal efficiency.

It is firmly established that contemporary building materials and indoor furnishings are associated with elevated concentrations of formaldehyde in indoor air, representing a hazard to human health. To mitigate this issue, formaldehyde and other pollutants in indoor air are removed via air conditioning systems fitted with appropriate filters. Based on positive results from earlier, relevant research, this study investigates the use of air conditioning filters treated with chitosan as potential eco-friendly absorbents for removal of formaldehyde, a significant indoor air pollutant. The filter is sprayed with different dosages of chitosan, in accordance with our previous work [8]. Removal rate and adsorption of formaldehyde are calculated for the health risk assessment. After twenty-four hours testing, the results showed the averaged concentration of formaldehyde is 1.146 ppm, 0.714 ppm, and 0.084 ppm with chitosan dosage of 2.6 mg m−2, 5.3 mg m−2, 8.0 mg m−2, respectively. The averaged reduction of formaldehyde concentration is 64.9%, 80.0%, and 96.0%; the averaged absorption of chitosan on formaldehyde is 0.167 mg, 0.204 mg and 0.271 mg for chitosan dosage of 2.6 mg m−2, 5.3 mg m−2, 8.0 mg m−2, respectively. The risk characterization figures without spaying chitosan are 2.94, 2.65 and 7.07 times higher when compared with the same figures associated with filters treated with 2.6 mg m−2, 5.3 mg m−2, and 8.0 mg m−2 of chitosan. This study finds that chitosan has strong potential as a commercial adsorbent. Increasing the amount of chitosan applied to the filter substrate improves the efficacy of the absorbent and further reduces the indoor formaldehyde concentration and the associated carcinogenic risk.

International audience; In practice, the elastic lateral-torsional buckling of doubly symmetric I-section steel members is analyzed assuming free warping at supports. However, welded stiffeners, bolted end-plate connections or column base plates maintain elastically the opposite flange out-of-plane rotations and thus induce substantial warping restraints.This paper proposes analytical formulations for the evaluation of the elastic critical bending moment for lateral-torsional buckling of beams taking into account warping restraints at supports. Assuming series of displacement and rotation fields containing one or two terms, the energy method permits to derive expressions of the critical bending moment under constant and linear distribution of the bending moment. A single expression of the warping coefficient kw is proposed whatever the shape of the bending moment diagram. The factor C1 can be conveniently calculated by multiplying two coefficients that depend on the shape of the bending moment diagram and on the warping restraint stiffness, respectively.Finite Elements analyses of beams with warping restraints at supports have been performed considering a beam element model developed with LTBeamN and a shell element model created in ANSYS. The analytical model is in good agreement with the numerical results obtained by the two finite element models.

The primary objective of university education is to provide students with the required information and skills to enable them to make a successful contribution to the national development effort. In order to evaluate the level of expertise and skill of students, this preparation includes frequent examination and appraisal in the form of tests. Manual exams are carried out by most universities; Post Graduate and Under Graduate in India. Due to multiple uses made of the outcomes of the students, these examinations have high stakes. Consequently, the experiments became subject to different types of malpractice. Test malpractice affects the success of students in exams and leaves the scores/grades earned inaccurate, hence a challenge to examination bodies and the nation's education system (India). These are all disturbing signs that pose a danger to the nation. Examination malpractice has eaten deep into the Indian culture of education. Therefore, the object of this paper is to explore the problem of examination malpractice in India. The paper covered relevant measures, procedure setting/implementation and suggestions for this action. And finally, a model is proposed to stop malpractices in the examination. This IoT based model is used for detecting any metallic object or object in a range more than normal IR proximity sensor range. The block diagram of proposed model and circuit diagram for that model discussed in detail. This proposed model may be used for any investigation in the universities examinations.

Smart materials have played significant contribution towards the development of buildings. There are various smart materials which can change their properties and behavior under the influence of external catalyst or stimulus. Such materials are changing the face of traditional engineering materials. Smart materials can be utilized individually as well as it can be incorporated with existing materials to enhance their desirable properties. Smart materials are widespread across all the domains of human inventions due to its multidisciplinary applications. Some of these materials are relatively new while some are being used from a very long time. Hence it suffices to say that the recently developed smart materials still require research. The general classification of smart material is illustrated in this review paper. The paper intends to identify the various types of available smart materials and also illustrated the application of such materials in the various fields of civil engineering. Further, the potential benefits and downsides are also discussed along with their applicability under different conditions. Some innovative materials are also discussed which can bring potential revolution in the construction industry. The impact or the benefits related to sustainability also discussed in this review paper.

In the recent years the utilization of cloud to store and process the big data is increased rapidly. Security is the major concern faced by the big data in cloud environment. This paper proposed the authentication scheme for preserving the security and privacy of the big data in cloud environment. This paper considered the medical big data processing from the telemedicine system as the big data. The medical big data consists of huge volumes of medical records which are stores in the cloud. In the proposed mechanism follows mutual authentication and performs encryption operation between user and cloud environment. The proposed authentication mechanism has less computational load compared to the existing algorithms.

This paper is a unique effort to resolve the scaling issues of machine learning using the multi-node environment of Big Data. For this purpose, it incorporates the concept of machine learning with big data. Machine learning is a branch of Artificial Intelligence which trains the computers to learn without being explicitly programmed. Machine learning works on the development of computer programs and software that work according to the input dataset. In machine learning, classification is used to identify the class of instances. In this the category or class or a group provides the new observation to which it belongs on the basis of the training dataset. Training datasets contain those instances whose class is already known. An algorithm that implements classification is known as a classifier. The main aim of this paper is to evaluate how different classifiers work on two different datasets, one is a real time dataset of MP Election nomination (2018), while the other is a standard Breast Cancer dataset, released by University of Wisconsin (1995). There are various classifiers available like Decision Trees, K-Nearest Neighbors, Support Vector Machine, Logistic Regression, Naive Bayes etc. Different classifiers work differently on different datasets, giving different accuracy according to the kind and the size of the dataset. So we have used different classifiers for our work. When we were applying machine learning classifier on a real-time dataset, i.e. MPSEC dataset, Accuracy goes down. Similarly, these classifiers apply to Standard Breast Cancer dataset then results show outstanding accuracy. This research work shows the exciting patterns to study the case of a real-time and standard dataset using different machine learning classifiers with a combination of big data. This research work also incorporates the concept of parallelization using a multi-nodes environment which is able to deal with scalability issues.

Road surface irregularities not only has an impact on consistency of road, but also affects driver safety, automobile mechanical stability, and fuel consumption. To order to evaluate road roughness and spot potholes, many solutions have been suggested to remotely track the road surface quality. Some of these methods use an embedded mobile accelerometer to take a crowd sensing view to feel the surface of road. Although crowd sensing has various advantages such as ubiquity and less cost, it has some sensitivity to the problems generated by structures made by human, actions of the driver, and characteristics of the road surface which cannot be identified road anomalies. For this purpose, this paper suggests method of deep learning which helps us (a) to identify the different types of surface of road and (b) to differentiate potholes automatically from destabilizations in the crowd sensing-based application sense arising from speed bumps or driver behavior. This paper study and implement different deep learning frameworks in particular: convolutionary neural networks, LSTM networks, and computational structures for reservoirs. The tests were performed using knowledge from the real world, and the results revealed good precision in solving both of the problems.

In this paper Telematics and employments of Telematics in vehicles is presented. Advancement is developing every year and is used by planners of the structure in various edges for the duration of regular day to day existence. Telematics system is making in different perspectives. Apparently it gives a lot of organizations in human lives. It makes life snappier and lessening setbacks in vehicle. Telematics data gives the reason to perceiving how far, how rapidly and underneath what conditions an individual drives, similarly as a foundation for logically propelled data showing improvement. This limit is developing new and innovative things that even more correctly esteem peril and attract beneficial new customers. By then, it explains how this structure works. It is like manner tends to the favored viewpoint and block of the system. This paper in like manner fuses the issues related to the telematics structure. Finally, it will see logical examination and wrap up this paper.

Over a last few decennary free space optical communication (FSO) have become more interesting alternative to the radio frequency for communication. The FSO is emanating technic that have been found the applications in different place of shorter & longer distance communication. The any technology, of FSO has been worked that much good in the several applications rather than other. In this paper we will examine FSO from different angles. The analyses this paper accompany of the technology has shown that FSO technologies inherent strengths and it lack the use of in ground cables which make it much expeditious & cheaper to installing, and the facts that will operates in the unlicensed spectrum, it will be removed & installed elsewhere and it has relatively high bandwidth. Specifically, this paper found that because FSO uses air as a communication medium, its performance & reliability are restricted by fog, rain, snow and dust. Maximum range of FSO may be in kilometers only. The applications that FSO technology seems most suited to is clear this pap rather and short distance connection establishment, like interrelation to broadband networks backbone & backbone links bet this papered building in the metropolitan area networks (MAN) or the campus area networks (CAN).

Blockchain has become one of the most developing technologies in our country. Blockchain technology is a decentralized, distributed ledger that records the sources of digital assets. Electronic Medical Record (EMR) accommodates patient’s medical history, which has been carried out by a Physician or Doctor in a particular clinic or hospital or Healthcare center. Whereas, Electronic Health Record (EHR) holds patient’s entire health history, including immunization plans, diagnosis, lab reports, inoculation schedule, etc.,. This feature empowers the usage of Health IT in a more secure way with the amendment of blockchain technology. These records are maintained smart contract between the patient and the healthcare sector. In both EMR and EHR, the patient is the owner of his own data. This paper incorporates the features of blockchain technology to provide a collaborative work on Electronic Medical Records (EMRs) and Electronic Health Records (EHRs) and it concentrates highly in diabetes as it has a sharp magnification in current world. Though it is tedious to implement this EHR all over the country, this paper works for its implementation especially in the domain of diabetes.

Mobile Ad-hoc networks (MANET) is a collection of nodes of wireless connectivity. In Mobile Ad hoc Network (MANET) all the mobile nodes are requiring restricted battery capacity. Because of the changing nature of network the sudden communication link breakage happens. Hence the possibility of data loss is more. Efficient utilization of energy and lossless transmission are the important issues in MANET. This paper proposes a new Trust based Efficient Energy Balanced Less Loss Routing (TER) Protocol for MANETS. This protocol improves the network performance by properly choosing the intermediate forwarding nodes. The Source Node picks only single of its neighbors as its next hop node by using Efficient Parameter (EP). The EP is calculated from the residual energy, distance, Occupied Queue space, the velocity of that node. The node using maximum EP is nominated as the succeeding node. This protocol reduces the number of channeling messages and hence reduces the path-finding Overhead of the network. It lessens the chance of data loss and hence improves throughput and Packet Delivery Ratio. This protocol adds trust to the selected node. In this paper, we do the simulation in ns-2 simulator and the performance is measured by with performance parameters like Routing Overhead, Packet Delivery Ratio, Throughput, End to End Delay and Average energy consumption.

The main purpose of this paper is to observe the effect PV variation of solar temperature and irradiance on different conditions and on the inverter output for a grid-connected system. Majorly temperature& solar irradiation effects the performance of a grid connected inverter, also on the photo-voltaic (PV) electric system. The simulation based study was carried out in order to evaluate the variation of inverter output with the variation of solar temperature and irradiance with the variation in climate. The analysis of Grid-connected inverter and their performance at various seasons and conditions is investigated. Solar power plant for a year. In solar power plant efficiency of inverter is also considered to calculate overall losses so, the inverter efficiency and plant performance are considered in this paper using MAT Lab software. In summer season the inverter performed efficiency is decreased because of peak temperature value and slightly increased with the increase in irradiance.

The power transmission tower’s ground electrode defect will affect its normal current dispersion function and threaten the power system’s safe and stable operation and even personal safety. Aiming at the problem that the buried grounding grid is difficult to be detected, this paper proposes a method for identifying the ground electrode defects of transmission towers based on single-side multi-point excited ultrasonic guided waves. The geometric model, ultrasonic excitation model, and physical model are established, and the feasibility of ultrasonic guided wave detection is verified through the simulation and experiment. In actual inspection, it is equally important to determine the specific location of the defect. Therefore, a multi-point excitation method is proposed to determine the defect’s actual position by combining the ultrasonic guided wave signals at different excitation positions. Besides, the precise quantification of flat steel grounding electrode defects is achieved through the feature extraction-neural network method. Field test results show that, compared with the commercial double-sided excitation transducer, the single-sided excitation transducer proposed in this paper has a lower defect quantization error in defect quantification. The average quantization error is reduced by approximately 76%.

This study examines how scientists respond to visual design in scientific communications. Specifically, we determine the impact of visual design on the Graphical Abstract (GA), an overview figure that attracts potential readers and visually summarizes what a paper is about. We show that GAs designed in accordance with classic visual design principles significantly enhance readers’ first impressions of a paper. Well-designed GAs make papers seem more interesting, more clearly written and more scientifically rigorous. These results confirm that visual design enhances rather than detracts from the perception of intellectual and scientific competence.

In the current era, Artificial Intelligence is playing a major role in smart devices. Apart from incorporating intelligence in the devices, it has extended its range beyond that. Now new AI development tools such as automated machine learning (AutoML) approach are increasing rapidly because of its performance on smart devices. AutoML is used to design a machine learning model with self-adapting capability which can perform the task in less time with advanced skills. This approach does not need any explicit coding and the data science experts but this can build smart sensor codes that will get executed automatically on the microcontrollers embedded within the IoT devices. Due to these capabilities, the developers can build efficient smart devices with real-time responsiveness, security, and data privacy without the help of machine learning experts. In this paper, we will show how AutoML will be used to create smart de-vices. The objective of this paper is to develop the skills that will help to develop smart edge devices which include planning, design-ing, implementation, and the evaluation of the smart IoT applications.

The present for supporting in market any industries need to bring the balance among ecological, social viewpoints and efficient. Environmental friendly machining e.g. high pressure cooling, MQL machining, cryogenic machining, dry machining is one of the latest approach which is economical and also eco-friendly that improve machinability. In present article main focus on understanding of environmental friendly machining techniques and investigate various experiences from the past writing which can help the better appropriation of ecological friendly machining approach. For study and examination of environmental friendly machining approach, roughly 100 papers are chosen. They chose articles are ordered dependent on climate of machining, year, diaries, distributor, and ecological friendly machining approach measurements. After the literature survey it was observed that in metal cutting operation heat are generated in the cutting zone due to tool chip interface so quality of surface finish are poor and tool wear. In any manufacturing industries two factors play important role in term of quality e.g. surface roughness and tool wear so in this situation some techniques are need which is environmental friendly and also improve machinability. So finally, it was observed that environmental friendly machining techniques are cost effective and eco-friendly machining compared to other convention machining approach. The main motives of this paper that studies and encourage environmental friendly machining approach.

The demand and supply gap of energy is large and the people are pressured to bear increasing hours of load losing, unnecessary intake of energy makes subjects even worse. So, the importance and requirement for energy conservation is increased exponentially. This paper outlines a step towards the conservation of electricity in standard and electricity especially with the aid of employing efficient constructing system with automation and installation of renewable based Micro Distributed Generator (MDG). The Smart Grid (SG) is a technological transformation from conventional electric grid, electro-mechanically controlled system, to smart, intelligent, and electronically controlled system. There are about 20–30% losses present in the conventional electric grid due to substandard operations at generation, transmission and distribution side. MDG play important role to build an efficient and autonomous micro-grid. In this paper importance of microgrid and some renewable energy sources utilized in formation of microgrid are discussed.

HRES (hybrid renewable energy systems) are an amalgamation of traditional and renewable sources that strive to overcome the intermittent nature of renewable energy production sources. The paper aims to provide a critical analysis of the capabilities and limitations of various software to assess HRES. The analysis cycle from design to optimization is an extremely complex task due to the many parameters being considered and has to be done thoroughly. Thus, the use of correct software to obtain comprehensive analysis is critical as it leads to minimal limitations in terms of cost, implementation, and maintenance of the system. When compared to traditional systems, hybridization can reduce costs and emissions by an estimated 20%. The software reviewed are the most widely used and comprehensive for HRES. Yet, they all come with their limitations. For example, HOMER is incapable of conducting a thermal analysis while only HOMER and IHOGA can conduct hydro energy sources analysis. As such, the paper aims to provide an in-depth review of the capabilities and limitations of various software regarding HRES, so that users can decide which software (both individually and in combination with each other) would be most appropriate for their HRES.

The concept of utilizing industrial and agricultural waste materials in concrete contributes to recompensing lacking natural resources, solving the waste disposal problem, and finding alternative techniques to protect nature. Environmental awareness regarding potential harmful effects has significantly increased, and, thus, recycling or using agricultural and industrial waste by-products has become an increasingly attractive alternative for waste disposal. Several related studies investigated the utilization of waste materials and by-products like coal bottom ash, rice husk ash, coconut shells, plastic, glass, and wood. In this paper, a thorough assessment has been conducted about the industrial and agricultural waste substances that can be effectively utilized in concrete as an alternative to cement or aggregate in the concrete mixture. This paper also aims to promote utilizing wastes by improving pozzolanic performance and material properties as part of concrete constituents.

In this research paper, our main focus is to design and develop a system for classification and recognition methodology for the acknowledgment and retrieval of a Sunflower flower in the natural environment centralized on the indigenous habitat dependent on a multi-layer method. Further, we design applications for their better classification. To handle a difficult undertaking task, an interdisciplinary cooperation is displayed dependent in the latest advancement methods in software implementation in engineering and innovation implemented by machine learning. A proposed work is design to increase the strategy for utilizing the techniques of machine learning. Final utilization of the Texture Feature, RST-Invariant Feature, Pattern Classification and furthermore utilize the K-Closest Neighbor calculations is done. Firstly, the paper is proposes to study about how to gather a flower images from the natural environment along with their corresponding background and Secondly, the paper focus on the Sunflower classification utility through Machine Learning. The computerization methods through blossom utilizing through AI system for sunflower utilized the 6-types of sunflower to get the fine yielding of profoundly sprouted sunflower blooms is caught from an advanced camera with a picture. The process of recognition implemented carried with 280 pictures. This method used a recognition as well as classification of sunflower by using the k-nearest neighbor image having overall 88.52% accuracy. This designed research paper, we trained the model with information and when concealed information is achieved then the predictive model predicts the Sunflower recognition through trained data supervised technique with machine learning.

Wind and solar green energy sources have increasingly been widely used by businesses and researchers worldwide. In the literature, these energy sources have also been represented. For these developments to be universal, these energy sources need more construction costs, more maintenance costs, and more operating space. An energy storage system is to be built to solve these issues, allowing us to store energy during lean hours and supply energy at a low cost later. These technologies, such as the battery, cell, and supercapacitor, can very easily store energy and energy distribution speeds. This energy sources have a high current for a limited period. We need electrode material and electrolyte material mentioned in previous research papers to make these energy sources. Due to its excellent electrical conductivity, excellent stability, and high specific surface area, electrode materials such as carbon and carbon-based materials are generally used. In these energy sources, these materials serve as dielectric materials. Carbon and carbon-based materials have recently been derived from bio-waste materials. These bio-waste products are bio-waste for agriculture, bio-waste for tree leaves and bio-waste from fruits. The use of these bio-waste products aids in the disposal of waste and turns waste into a vital resource. These products for bio-waste are readily available at no cost. The approaches used by researchers to obtain from bio-waste are explored in this study research paper on the availability of different bio-waste materials.

Tropical cyclones represent one of India's toughest natural threats. This paper lists the challenges and mitigation efforts to resolve significant disasters in the coastal areas of eastern India in particular. Humans must learn to counter and live with the effects of such natural disasters as they are unavoidable . The construction of natural hazard structures has always been supported by various national and international disaster mitigation organisations. New building design standards are proposed, as planning and growth to reduce the possibility of potential structural damage. Damage is caused to the roof, walls, openings, and foundation of a building due to the use of non-disaster proof construction practices. A brief introduction on the damaging effects of noteworthy cyclones is provided. It has been highlighted the increasing frequency of cyclones since the start of the 21st century due to climate change. A focus is maintained on the challenges faced by rural regions of India for the eastern coastline especially in the housing sector. Climate change and further cyclones have caused the loss of crops and thus livelihood, which is the main concern for the rural people. A section on the challenges to the housing reconstruction provisions for the rural community, as provided by the Government of India is depicted. Lastly, the paper provides various solutions for a cyclone-resistant structure and disaster prevention as per the challenges faced by the rural community.

A proposed method for automation of Indian vehicles number plate conversion is presented in this paper. Many vehicles are plying on Indian roads with varying in size and structure and hence there are a number of variations in number plates too. Although there are strict norms to be followed for number plate designs, however, it can be seen many deviations in actual number plates of many vehicles. It can be also observed that the number plates are written in many Indian languages, but the prescribed norm is Hindu-Arabic numerals with Latin letters which is prescribed by the licensing plate issuing authority. The number plate designs are varied according to types of vehicles, like, personal, commercial, public transport, etc. In order to design an automatic vehicle number plate, considerations of these factors are taken into account. The steps in the design include segmentation and character extraction from number plates and recognition of segmented characters in order to extract the complete information from number plates. The work in this paper is focused on Hindu-Arabic numerals with Latin letters. For feature extraction, Prewitt filter technique is used to extraction of characters from the vehicle number plates and connected component analysis is used for segmenting characters. Three different classifiers, namely, k-Nearest Neighbor, Artificial Neural Network and Decision Tree, are used in the experiments. Recognition accuracy up to 98.10% is achieved and is a promising factor for future research in this direction.